Inference.net · language model
Schematron V2 Turbo: pricing, context and benchmarks
Schematron V2 Turbo is a language model from Inference.net released on September 12, 2026. It costs $0.03 per million input tokens and $0.15 per million output tokens, with a 128K-token context window. No independent score has been published for it so far.
What you need to know about Schematron V2 Turbo
Schematron V2 Turbo was released by Inference.net (United States) on September 12, 2026. It accepts text as input and produces text. Its context window reaches 128,000 tokens, larger than 19 % of the models in the registry, and it can write up to 8,192 tokens in one go.
It is a recent model: real-world feedback and independent scores are still scarce.
Schematron V2 Turbo pricing
On OpenRouter, Schematron V2 Turbo costs $0.03 per million input tokens and $0.15 per million output tokens. Counting three tokens read for every token written, its average price is $0.06 per million, more expensive than 4 % of paid models (12.7 times cheaper than the median of $0.76).
A concrete example: a task that sends 2,000 tokens (about 1,500 words) and receives a 500-token answer costs $0.0001. At 1,000 tasks a day, budget $4 a month. The price calculator redoes this with your own volumes.
Tokens already sent and cached are billed at $0.03 per million.
Performance and benchmarks
Epoch AI does not yet publish a capabilities index for Schematron V2 Turbo. We therefore show no made-up performance rating: only price, context and features count towards its score.
Features, privacy and local use
- It does not support tool calling: it is not suited to driving an AI agent that has to act.
- It can answer in an enforced JSON format (structured outputs).
Its weights are open and downloadable from Hugging Face: you can run it on your own machines without sending your data to a third party.
Other Inference.net models
| Model | Released | Avg. price | ECI |
|---|---|---|---|
| Schematron V2 Small | Sep 12, 2026 | $0.1 | — |
Verdict
Schematron V2 Turbo scores 65/100 on our grid, which only uses published figures.
Strengths
- Low price: cheaper than 96 % of paid models.
- Open weights: self-hostable, your data stays with you.
Limitations
- No tool calling: unusable as an agent's brain.
- No independent score published: performance cannot be verified.
- Text only: reads neither images nor files.
Avoid if…
- you are building an agent that must call tools.
Alternatives
- Command R7B (12-2024)$0.07
- Nova Micro 1.0$0.06
- Granite 4.0 Micro$0.04
- Gemma 3 12B$0.08
- Llama 3.2 1B Instruct$0.07
- Llama 3.1 8B Instruct$0.06
Comparisons and tools
Learn more
Frequently asked questions
How much does Schematron V2 Turbo cost?
$0.03 per million input tokens and $0.15 per million output tokens on OpenRouter (checked October 25, 2026). A task with 2,000 tokens read and 500 written costs $0.0001.
How big is Schematron V2 Turbo's context window?
128,000 tokens, roughly 96,000 words, with a maximum of 8,192 output tokens.
Can Schematron V2 Turbo run locally?
Yes, its weights are published.
Is Schematron V2 Turbo suitable for an AI agent?
No: without tool calling it cannot act, only answer.
What are the alternatives to Schematron V2 Turbo?
The closest models on price and performance are Command R7B (12-2024), Nova Micro 1.0, and Granite 4.0 Micro.
Related articles
- Mistral AI: models, pricing and agentsOctober 25, 2026
- LLM benchmarks: how to read model rankingsOctober 24, 2026
- Running a local LLM: hardware, software, and limitationsOctober 24, 2026
- Open-source or closed models for your AI agents?October 5, 2026
Neutrality. No affiliate links. No vendor pays to be reviewed, rated or ranked. Reviews are directed by François Chollet, neutral and factual, and every data point is dated and sourced. How we score